123 citations · 301 across the 20 of their papers we have counts for
8 papers · 1 filter
Random graphical model of microbiome interactions in related environments
Veronica Vinciotti, Ernst Wit, Francisco Richter
The microbiome constitutes a complex microbial ecology of interacting components that regulates important pathways in the host. Measurements of microbial abundances are key to lear…
Mixtures of multivariate generalized linear models with overlapping clusters
Saverio Ranciati, Veronica Vinciotti, Ernst C. Wit +1
With the advent of ubiquitous monitoring and measurement protocols, studies have started to focus more and more on complex, multivariate and heterogeneous datasets. In such studies…
Model-based clustering for populations of networks
Mirko Signorelli, Ernst Wit
Until recently obtaining data on populations of networks was typically rare. However, with the advancement of automatic monitoring devices and the growing social and scientific int…
Dynamic Chain Graph Models for Ordinal Time Series Data
Pariya Behrouzi, Fentaw Abegaz, Ernst C. Wit
This paper introduces sparse dynamic chain graph models for network inference in high dimensional non-Gaussian time series data. The proposed method parametrized by a precision mat…
Estimating Causal Effects From Nonparanormal Observational Data
Seyed Mahdi Mahmoudi, Ernst Wit
One of the basic aims in science is to unravel the chain of cause and effect of particular systems. Especially for large systems this can be a daunting task. Detailed interventiona…
Bayesian Smooth-and-Match strategy for ordinary differential equations models that are linear in the parameters
Saverio Ranciati, Cinzia Viroli, Ernst Wit
In many fields of application, dynamic processes that evolve through time are well described by systems of ordinary differential equations (ODEs). The analytical solution of the OD…
Penalized EM algorithm and copula skeptic graphical models for inferring networks for mixed variables
Fentaw Abegaz, Ernst Wit
In this article, we consider the problem of reconstructing networks for continuous, binary, count and discrete ordinal variables by estimating sparse precision matrix in Gaussian c…
Joint modelling of ChIP-seq data via a Markov random field model
Yanchun Bao, Veronica Vinciotti, Ernst Wit +1
Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein binding sites. In this paper, we present a Markov ra…